Skripsi

DETEKSI EXPLOIT REVERSE HTTPS DENGAN METODE LOGISTIC REGRESSION

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Reverse HTTPS attacks conceal malware communication within encrypted traffic. This research detects these threats using the Logistic Regression method on raw data from the Mobile-Trojan Metasploit Traffic. The data flow feature extraction results obtained through the CICFlowMeter tool are crucial for preserving the dataset's overall quality. Modeling was conducted without resampling techniques to maintain natural class imbalance, while class labeling utilized dynamic analysis from Suricata. Testing on an 80:20 data split scenario showed highly optimal performance with 98.52% accuracy and a 98.52% F1-score. The recall rate reached 100% (Zero False Negative), ensuring all attack activities were successfully detected without any being missed. This method is proven reliable in securing and classifying network traffic. This solution is highly effective and efficient.

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Detail Information

Series Title

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Call Number

T1949222026

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2026

Collation

x, 111 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

333.761 507

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Prodi Sistem Komputer
Pembelajaran Mesin

Specific Detail Info

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Statement of Responsibility

KA

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